Receiver Types

GNSS receivers can be categorized by their type in different ways, and under different criteria. Besides the professional-grade receivers (e.g. survey and precision), commercial Portable Navigation Devices (PND's) are very common inside vehicles today, and smartphones appear more and more equipped with integrated GNSS receivers. These receivers are implemented in a wide variety of platforms, from ASIC, DSP or FPGA, to general purpose microprocessors. The choice of the target platform is often a trade-off of parameters such as receiver performance, manufacture and maintenance cost, expandability, power consumption, and autonomy. Some of the differentiating applications and receiver implementations, differing in a number of design decisions and approaches to GNSS solution computation, are described in the following topics.

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Multi-constellation

With the emergence of multiple satellite navigation systems (both regional and global), multi-constellation receivers are becoming widely available. This has been encouraged at system design level by working towards interoperability and compatibility among all systems, allowing for seamless combination of the different signal spectra and processing chains into a single, multi-constellation GNSS solution. This approach reflects on the four global GNSS receiver implementations:

From the receiver perspective, multi-constellation brings a key added value on solution availability, especially in urban environments: with the increased number of constellations available, the number of satellites visible to the user is bound to increase. This allows several algorithm implementations to be further refined, and the final solution can be computed with higher accuracy and availability (for instance, see the improvements due to higher availability in Dilution of Precision (DOP)).

Multi-frequency

Several GNSS signals are allocated to different frequencies - for instance, the L1 and L2 bands. Whether in single or multi-constellation approaches, receivers can benefit from multi-frequency signal processing for removal of the frequency-dependent errors on the signals, hence improving receiver accuracy. The most important example is the correction for ionospheric delays, since these usually represent the main contributors to the overall measurement error.

Multi-frequency receivers, however, bring forth a new challenge, since there is a need for increasing RF hardware sections. Typical antennas, front ends, and filtering/sampling circuits are centred on one of the desired frequencies, and in most cases the same amount of RF hardware is replicated for the other frequency (or frequencies) to process. For this fact, there is also trade-offs implied between cost, size, power consumption, performance, signal and band filtering, and analogue circuitry quality.

Augmentation

GNSS receivers can also benefit from corrections or measurements provided by the available augmentation systems to improve their accuracy and performance. As the name implies, such systems aim at providing augmentation information to the GNSS users, consisting of corrections and/or auxiliary measurements that increase precision and accuracy in the calculated solution. As examples of receivers that use satellite augmentation information, see:

Differential

Differential techniques enable improved receiver accuracy by providing the receiver with additional information, such as measurements from other receivers in the vicinities, or corrections computed independently. Such external information is then used within a receiver in a differential way, e.g. improving the solution accuracy. Some of the most widely used differential techniques available in current receiver technology are:

Assistance

The definition of assisted-GNSS[1] (A-GNSS) gathers many different concepts, but can be split into two main categories:

GNSS assistance information is used to improve acquisition speed: an assistance network - comprised of servers and information relays - transmits almanac and/or ephemeris data to the receiver, so that the initial search for satellites can be performed faster. This allow the receiver to start tracking visible satellites quicker, thus providing a navigation solution in less start-up time.

Data processing and solution computation is performed in the server: in this case, the receiver can send measurements like visible satellites, pseudoranges or phase information to the servers, where the heavier computational load for generating an accurate solution is performed, and the results are sent back to receiver.

The assistance information can be accessed by the receiver beforehand (e.g. via Internet), or received on request (usually through wireless communications)[2]. So, assisting information can be provided by different technologies, such as Wi-Fi, GPRS/UMTS, or the internet. Depending on the solution envisaged, this might have an impact at several levels, such as availability, continuity, and power consumption. As an example of assisted data, the International GNSS Service provides position, velocity and clock information regarding GPS satellites that GNSS receivers can use to improve accuracy.

Assistance data is also used in indoor[3] environments, where receivers struggle to get anything out of GNSS. These environments are very stringent in terms of GNSS signal reception, and the solutions often include integrating different sensors and technologies to use all available data to provide a navigation solution.

Software receivers

Figure 1: Hardware vs. Software receiver approaches.

Besides the wide variety of hardware platforms and their evolution, the so-called “software receivers”[4] have proliferated lately, thanks to its additional flexibility, reconfiguration capabilities, upgradeability and expandability.

The concept behind a software receiver is depicted in Figure 1, which identifies the key processing blocks of a GNSS receiver, and shows the differences in approach between hardware and software implementations. Since the algorithmic and signal processing tasks are performed in software, there is an added control and flexibility on the tasks performed. Also, future changes in algorithms or approaches are easier in a software approach.

One identified drawback in a software implementation of a receiver, however, is the efficiency concerning the processing load, specifically its impact on a CPU power consumption in mobile platforms[5].